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AI agents keep long-term memory, much of which comes from web pages and tool results. Agent harnesses, the software that runs the model, do not record who may act on this memory, so an instruction hidden in a fetched page can be treated as the user's own instruction. We propose ClawMMU, a protection layer that labels e...
Recent work uses large language models to generate systems code from specifications, treating the specification as the durable artifact and the implementation as disposable. Regenerating the implementation specializes it to each workload and device. However, that work lives in a forgiving setting: a component's externa...
Tests play two roles in automated program repair (APR): they are the evidence that accepts a patch, and they are repository artifacts that may themselves need repair. Benchmarks resolve the tension by making evaluator-owned tests immutable; deployment cannot, because tests legitimately evolve with the code they check....
A guarded-commit design that makes human approval part of workflow state and supports audit and replay under the policy in force when the resolution was recorded is presented.
Recourse is designed, a smart-contract settlement protocol for compensable agent side effects that binds each admitted action to scope, recovery, evidence, payout, and collateral, and separates ex ante eligibility from ex post objective settleability.
This work reconstructs a coupled-fact graph as reconstructing a coupled-fact graph: at each edit, a required fact comes from recent context or parametric memory, and the facts covered by neither form coherence debt.
The Agent Flight Recorder captures each agent action as a structured, canonically serialized event binding eight semantic fields from intent through execution to provenance, and periodic on-chain anchoring of epoch roots lets any verifier with the disclosed payload and Merkle proof check the record independently, witho...
Large language models (LLMs) can implement row-level semantic transformations over tabular data, but a general-purpose model reserves the same accelerator resources even when every row uses one fixed prompt. IOLM-DB compiles that recurring prompt–column pair into an operator sized to the work it actually does. It sampl...
The irreversibility budget is proposed, a cumulative account of residual value-at-risk that a trusted runtime maintains for each principal across agents, workflows, and tenants.
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